caa a22 4500 465825885 CHVBK 20180323112148.0 cr unu---uuuuu 170327e19901001xx s 000 0 eng 10.1007/BF02842489 doi (NATIONALLICENCE)springer-10.1007/BF02842489 Recognition accuracy with a voice-recognition system designed for anesthesia record keeping [Elektronische Daten] [N. Smith, Robin Brien, Daniel Pettus, Brian Jones, Michael Quinn, Andrew Sarnat] We tested on three occasions, with anesthetists as subjects, the accuracy of two voice-recognition systems designed for anesthetic record keeping. Initially, a prototype system was tested (10 subjects); several years later the resulting commercial system was tested in a quiet environment (11 subjects) and in noisy operating rooms (10 subjects). For each test an anesthetist first trained the system to recognize his or her voice by reading aloud a list of common anesthetic terms. To determinerecognition accuracy, the percentage of words recognized correctly by the computer, each subject repeated the vocabulary words ten times. Although accuracy was similar during the three tests, it was slightly higher with the laboratory test (mean percent of words recognized correctly, 96.5%; range of accuracy for individual anesthetists, 91.6 to 98.8%) than with the prototype test (95.9%; range, 89.1 to 99.6%). Accuracy was lowest with the operating room test (95.3%; range, 87.8 to 98.4%). Twenty-four words caused particular difficulty during the laboratory test and were eliminated from the vocabulary of the subsequent operating room test. Omitting these 24 words from the laboratory vocabulary list allowed a more nearly direct comparison with the results from the operating room list; recognition accuracy improved in the former to 97.5% (range, 92.1 to 98.9%). Two anesthetists—one each from the laboratory and operating room tests —performed poorly, and eliminating their scores changed the respective overall scores to 98.2% (range, 96.7 to 98.9%) and 96.5% (range, 94.3 to 98.4%). Thus, the corrected difference between the laboratory accuracy and the operating room accuracy was 1.7%. We conclude that about 90% of anesthetists can achieve usable recognition accuracy with the current voice-recognition system, even with no previous experience with the system. Little, Brown and Company, 1990 Records: anesthesia nationallicence Monitoring: Automated record keeping nationallicence Smith N. Department of Anesthesia, University of California, San Diego aut Brien Robin Department of Anesthesia, University of California, San Diego aut Pettus Daniel Diatek, Incorporated, San Diego, CA aut Jones Brian Department of Anesthesiology, University of California, Davis, CA aut Quinn Michael Department of Anesthesia, University of California, San Diego aut Sarnat Andrew Department of Anesthesia, University of California, San Diego aut Journal of Clinical Monitoring Springer Netherlands 6/4(1990-10-01), 299-306 0748-1977 6:4<299 1990 6 10877 https://doi.org/10.1007/BF02842489 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF02842489 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Smith N. Department of Anesthesia, University of California, San Diego aut NATIONALLICENCE 700 1- Brien Robin Department of Anesthesia, University of California, San Diego aut NATIONALLICENCE 700 1- Pettus Daniel Diatek, Incorporated, San Diego, CA aut NATIONALLICENCE 700 1- Jones Brian Department of Anesthesiology, University of California, Davis, CA aut NATIONALLICENCE 700 1- Quinn Michael Department of Anesthesia, University of California, San Diego aut NATIONALLICENCE 700 1- Sarnat Andrew Department of Anesthesia, University of California, San Diego aut NATIONALLICENCE 773 0- Journal of Clinical Monitoring Springer Netherlands 6/4(1990-10-01), 299-306 0748-1977 6:4<299 1990 6 10877 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer